クエリ駆動型通信効率の高い自動運転向けデジタルツイン設計
A Query-Driven Communication-Efficient Digital Twins Design for Autonomous Driving
自動運転のデジタルツイン構築において、冗長なデータ同期を避けるため、シミュレーション結果に基づいて必要な環境データを能動的に要求するクエリ駆動型アーキテクチャを提案し、通信効率と位置精度を改善した。
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著者: Nuocheng Yang, Longyu Zhou, Sihua Wang, Changchuan Yin, Tony Q. S. Quek
分類: cs.RO, cs.AI
原文アブストラクト
Digital twins (DTs) have become a potential technology to perform risk-free simulation of physical entities for deterministic and high-reliability services in diverse scenarios such as autonomous driving and low-altitude economy. In the autonomous driving scenario, traditional DT methods that rely solely on vehicle's real-time state synchronization, however, might lead to unacceptable computing and communication consumption for construction of high-fidelity DT with redundant data. To address this issue, we first propose a query-driven DT architecture to enable the DT to actively request the desired environment data from vehicles based on its simulation result. Then, we formulate an optimization problem whose goal is to minimize autonomous driving position error while accounting for DT fidelity and communication constraints. We also design a cross-time-step progressive query mechanism to further improve communication efficiency. The simulation results show that our proposed method achieves a 24% reduction in planning position error compared to traditional methods, while reducing communication overhead by 40%.
関連論文
- 学習型自動運転車の交通標識認識に向けたデジタルツイン試作自動運転/デジタルツイン
- 自動運転のためのスマートモビリティデジタルツイン：設計と概念実証自動運転/デジタルツイン
